Method to filter ECGs and evaluate clinical parameter distortion using realistic ECG model parameter fitting
By fining a previously published nonlinear model for generating realistic ECG to waveforms collected from a healthy human subject, and using a nonlinear leastsquares optimization procedure, the authors demonstrate that significant points (P, Q, R, S, and T) on the ECG can be determined to an arbitra...
| Main Authors: | , |
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| Format: | Journal article |
| Language: | English |
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2005
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| _version_ | 1826282262959751168 |
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| author | Clifford, G McSharry, P |
| author_facet | Clifford, G McSharry, P |
| author_sort | Clifford, G |
| collection | OXFORD |
| description | By fining a previously published nonlinear model for generating realistic ECG to waveforms collected from a healthy human subject, and using a nonlinear leastsquares optimization procedure, the authors demonstrate that significant points (P, Q, R, S, and T) on the ECG can be determined to an arbitrary accuracy. The model-fitting routine runs in real-time on a 3GHz PC. Coloured (1/fβ) noise is then added to the ECG in order to evaluate the fitting accuracy under a variety of recording conditions. A method for determining noise levels (and colour) in real ECGs using the residual of a singular valued decomposition is described. Furthermore, a method for evaluating the filter is described which allows an application-specific evaluation of the filter in terms of the distortion in the QRS width and amplitude, the ST-level, the QT interval, the PR-interval, and the fiducial point location. Using these methods, the model-based filter is shown to introduce insignificant clinical distortion in the QT interval and QRS width down to an SNR≥ 0dB for β < 2. The fiducial point location is shown to be insignificantly distorted (< 1ms) for an SNR≥ 2dB, and the ST-level is stable down to SNR> 12dB. PR interval is more sensitive to noise due to the low amplitude nature of the P-wave. In general, the filter performance is degraded by increasing β. © 2005 IEEE. |
| first_indexed | 2024-03-07T00:41:11Z |
| format | Journal article |
| id | oxford-uuid:8316ecc3-4e4a-4a5e-af41-28ef0b3427ba |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T00:41:11Z |
| publishDate | 2005 |
| record_format | dspace |
| spelling | oxford-uuid:8316ecc3-4e4a-4a5e-af41-28ef0b3427ba2022-03-26T21:41:55ZMethod to filter ECGs and evaluate clinical parameter distortion using realistic ECG model parameter fittingJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:8316ecc3-4e4a-4a5e-af41-28ef0b3427baEnglishSymplectic Elements at Oxford2005Clifford, GMcSharry, PBy fining a previously published nonlinear model for generating realistic ECG to waveforms collected from a healthy human subject, and using a nonlinear leastsquares optimization procedure, the authors demonstrate that significant points (P, Q, R, S, and T) on the ECG can be determined to an arbitrary accuracy. The model-fitting routine runs in real-time on a 3GHz PC. Coloured (1/fβ) noise is then added to the ECG in order to evaluate the fitting accuracy under a variety of recording conditions. A method for determining noise levels (and colour) in real ECGs using the residual of a singular valued decomposition is described. Furthermore, a method for evaluating the filter is described which allows an application-specific evaluation of the filter in terms of the distortion in the QRS width and amplitude, the ST-level, the QT interval, the PR-interval, and the fiducial point location. Using these methods, the model-based filter is shown to introduce insignificant clinical distortion in the QT interval and QRS width down to an SNR≥ 0dB for β < 2. The fiducial point location is shown to be insignificantly distorted (< 1ms) for an SNR≥ 2dB, and the ST-level is stable down to SNR> 12dB. PR interval is more sensitive to noise due to the low amplitude nature of the P-wave. In general, the filter performance is degraded by increasing β. © 2005 IEEE. |
| spellingShingle | Clifford, G McSharry, P Method to filter ECGs and evaluate clinical parameter distortion using realistic ECG model parameter fitting |
| title | Method to filter ECGs and evaluate clinical parameter distortion using realistic ECG model parameter fitting |
| title_full | Method to filter ECGs and evaluate clinical parameter distortion using realistic ECG model parameter fitting |
| title_fullStr | Method to filter ECGs and evaluate clinical parameter distortion using realistic ECG model parameter fitting |
| title_full_unstemmed | Method to filter ECGs and evaluate clinical parameter distortion using realistic ECG model parameter fitting |
| title_short | Method to filter ECGs and evaluate clinical parameter distortion using realistic ECG model parameter fitting |
| title_sort | method to filter ecgs and evaluate clinical parameter distortion using realistic ecg model parameter fitting |
| work_keys_str_mv | AT cliffordg methodtofilterecgsandevaluateclinicalparameterdistortionusingrealisticecgmodelparameterfitting AT mcsharryp methodtofilterecgsandevaluateclinicalparameterdistortionusingrealisticecgmodelparameterfitting |